The Spatial Allocation Model is an effective way to map detailed patterns of crop production using much less specific input data. A variety of information sources are used to generate plausible, disaggregated estimates of crop distribution, which are useful for understanding production and land use patterns. Identifying where trends take place is important for understanding why they take place. Understanding the location of production relative to a country’s infrastructure, services, and other sectors will enable better planning, allocation of resources, and targeting of interventions. Knowing the detailed patterns of productivity will help diagnose and target underperforming areas.
The enhanced knowledge of agricultural production systems and associated livelihood strategies that spatially disaggregated crop data yield can form the basis of rural development strategies. Given the enormous diversity and site-specific nature of many African production systems—as well as their associated cultural, socioeconomic, and resource management issues—effective development strategies should account for such spatial patterns. These strategies require a framework that takes into account the opportunities and constraints of different development options within a specific geographic area, thus allowing policymakers to select the appropriate plan based on the area’s characteristics.
Using GIS to analyze production and productivity patterns offers ways to understand and manipulate how geography affects agriculture through policy interventions. SPAM’s outputs are also uniform in resolution and structure, meaning they are more easily introduced and manipulated within a GIS than the irregular structures of political or administrative boundaries in which statistics are usually compiled. Traditional statistical agricultural data does not allow for production shares to be calculated by agro-ecological zones that span geopolitical boundaries.
SPAM results have been widely used within and outside IFPRI. The model and its outputs are the key elements in the organization’s global change research, including the HarvestChoice program, climate change work, and regional research and development priority setting within IFPRI for East Africa and West. Analysts at the Consultative Group on International Agricultural Research (CGIAR) centers, the World Bank, the Food and Agriculture Organization of the United Nations (FAO), as well as researchers at universities and in developing country national agricultural research systems, have applied SPAM outputs in their work.
